We don't have a machine for us to test with both "--with-cuda --with-hip"
--Junchao Zhang On Wed, Jan 4, 2023 at 6:17 PM Matthew Knepley <[email protected]> wrote: > On Wed, Jan 4, 2023 at 7:09 PM Junchao Zhang <[email protected]> > wrote: > >> On Wed, Jan 4, 2023 at 6:02 PM Matthew Knepley <[email protected]> wrote: >> >>> On Wed, Jan 4, 2023 at 6:49 PM Junchao Zhang <[email protected]> >>> wrote: >>> >>>> >>>> On Wed, Jan 4, 2023 at 5:40 PM Mark Lohry <[email protected]> wrote: >>>> >>>>> Oh, is the device backend not known at compile time? >>>>> >>>> Currently it is known at compile time. >>>> >>> >>> Are you sure? I don't think it is known at compile time. >>> >> We define either PETSC_HAVE_CUDA or PETSC_HAVE_HIP or NONE, but not both >> > > Where is the logic for that in the code? This seems like a crazy design. > > Thanks, > > Matt > > >> Thanks, >>> >>> Matt >>> >>> >>>> Or multiple backends can be alive at once? >>>>> >>>> >>>> Some petsc developers (Jed and Barry) want to support this, but we are >>>> incapable now. >>>> >>>> >>>>> >>>>> On Wed, Jan 4, 2023, 6:27 PM Junchao Zhang <[email protected]> >>>>> wrote: >>>>> >>>>>> >>>>>> >>>>>> On Wed, Jan 4, 2023 at 5:19 PM Mark Lohry <[email protected]> wrote: >>>>>> >>>>>>> Maybe we could add a MatCreateSeqAIJCUSPARSEWithArrays(), but then >>>>>>>> we would need another for MATMPIAIJCUSPARSE, and then for HIPSPARSE on >>>>>>>> AMD >>>>>>>> GPUs, ... >>>>>>> >>>>>>> >>>>>>> Wouldn't one function suffice? Assuming these are contiguous arrays >>>>>>> in CSR format, they're just raw device pointers in all cases. >>>>>>> >>>>>> But we need to know what device it is (to dispatch to either >>>>>> petsc-CUDA or petsc-HIP backend) >>>>>> >>>>>> >>>>>>> >>>>>>> On Wed, Jan 4, 2023 at 6:02 PM Junchao Zhang < >>>>>>> [email protected]> wrote: >>>>>>> >>>>>>>> No, we don't have a counterpart of MatCreateSeqAIJWithArrays() for >>>>>>>> GPUs. Maybe we could add a MatCreateSeqAIJCUSPARSEWithArrays(), but >>>>>>>> then we >>>>>>>> would need another for MATMPIAIJCUSPARSE, and then for HIPSPARSE on AMD >>>>>>>> GPUs, ... >>>>>>>> >>>>>>>> The real problem I think is to deal with multiple MPI ranks. >>>>>>>> Providing the split arrays for petsc MATMPIAIJ is not easy and thus is >>>>>>>> discouraged for users to do so. >>>>>>>> >>>>>>>> A workaround is to let petsc build the matrix and allocate the >>>>>>>> memory, then you call MatSeqAIJCUSPARSEGetArray() to get the array and >>>>>>>> fill >>>>>>>> it up. >>>>>>>> >>>>>>>> We recently added routines to support matrix assembly on GPUs, see >>>>>>>> if MatSetValuesCOO >>>>>>>> <https://petsc.org/release/docs/manualpages/Mat/MatSetValuesCOO/> >>>>>>>> helps >>>>>>>> >>>>>>>> --Junchao Zhang >>>>>>>> >>>>>>>> >>>>>>>> On Wed, Jan 4, 2023 at 2:22 PM Mark Lohry <[email protected]> wrote: >>>>>>>> >>>>>>>>> I have a sparse matrix constructed in non-petsc code using a >>>>>>>>> standard CSR representation where I compute the Jacobian to be used >>>>>>>>> in an >>>>>>>>> implicit TS context. In the CPU world I call >>>>>>>>> >>>>>>>>> MatCreateSeqAIJWithArrays(PETSC_COMM_WORLD, nrows, ncols, >>>>>>>>> rowidxptr, colidxptr, valptr, Jac); >>>>>>>>> >>>>>>>>> which as I understand it -- (1) never copies/allocates that >>>>>>>>> information, and the matrix Jac is just a non-owning view into the >>>>>>>>> already >>>>>>>>> allocated CSR, (2) I can write directly into the original data >>>>>>>>> structures >>>>>>>>> and the Mat just "knows" about it, although it still needs a call to >>>>>>>>> MatAssemblyBegin/MatAssemblyEnd after modifying the values. So far >>>>>>>>> this >>>>>>>>> works great with GAMG. >>>>>>>>> >>>>>>>>> I have the same CSR representation filled in GPU data allocated >>>>>>>>> with cudaMalloc and filled on-device. Is there an equivalent Mat >>>>>>>>> constructor for GPU arrays, or some other way to avoid unnecessary >>>>>>>>> copies? >>>>>>>>> >>>>>>>>> Thanks, >>>>>>>>> Mark >>>>>>>>> >>>>>>>> >>> >>> -- >>> What most experimenters take for granted before they begin their >>> experiments is infinitely more interesting than any results to which their >>> experiments lead. >>> -- Norbert Wiener >>> >>> https://www.cse.buffalo.edu/~knepley/ >>> <http://www.cse.buffalo.edu/~knepley/> >>> >> > > -- > What most experimenters take for granted before they begin their > experiments is infinitely more interesting than any results to which their > experiments lead. > -- Norbert Wiener > > https://www.cse.buffalo.edu/~knepley/ > <http://www.cse.buffalo.edu/~knepley/> >
